Scalable learning of Bayesian network classifiers
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Scalable learning of Bayesian network classifiers
I present our work on highly-scalable out-of-core techniques for learning well-calibrated Bayesian network classifiers. Our techniques are based on a novel hybrid generative and discriminative learning paradigm. These algorithms – provide straightforward mechanisms for managing the bias-variance trade-off – have training time that is linear ...
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